Numerous studies have shown that minority groups often face discrimination when applying for loans. Usually, this results in higher interest rates or even outright rejection.
Artificial intelligence may provide a way for financial institutions to be more inclusive in their lending practices without taking on excessive financial risks. The usage of AI technology has the capacity to reduce labor costs, automate processes, and it may even be able to remove the human element of lending by basing decisions on data.
But how can banks and credit unions harness the power of AI to make smarter, more profitable lending decisions?
AI technology uses complex algorithms that allow financial companies to automate and undertake a number of processes. Empowered by Big Data, they can undertake sophisticated calculations and give surprisingly accurate results with a minimum error margin.
More inclusive lending is a win-win for all parties involved. For lenders, it combines a socially oriented strategy with a great marketing tool. Borrowers, even those with thin files, get a better chance to receive financing at a reasonable price. For the financial industry as a whole, expanded access to finance without compromising the financial stability of lenders and borrowers looks like a great match.
Critics of AI focus on the quality of the data being used, saying that there’s the potential for the technology to become biased when algorithms use faulty data to reach conclusions, or work in areas where not enough data is available (such as less competitive environments or low-shopping behavior). This can occur in underbanked communities.
Henry Ford once said, “Failure is only the opportunity to begin again, only more wisely this time.” Recognizing the initial challenges in AI technology, we can move forward more fairly and intelligently. By knowing the obstacles, financial services providers can adapt solutions in smarter ways to target and reduce instances of bias in lending.
Here are some of the ways AI can be adapted to facilitate fairer lending.
Allowing access to a broader range of financial products
Previously, the variety of lending products on the market was limited by the methodologies used to calculate risk and assess data. The capabilities of Big Data now allow companies to expand this list, tailoring their services to meet the needs of the actual market. For those who find challenges in accessing credit, this offers the possibility to tailor services and repayment more accurately while lowering the risk for the lender.
Automat internal services to allow more client focus
From filling in the application form to managing an account to organizing repayments and calculating risk, AI empowers companies to automate processes to make them faster than ever before. This allows financial institutions to focus on customers more intensely. This can mean everything from consulting on the best loans available for the particular client to ensuring less risk for the lender if something is off with the client’s data.
Streamlining the applications process to make it more accessible
For some from minority backgrounds, the process of applying for a loan itself becomes an impediment. Complicated language and endless forms create inaccessibility, and some give up before completing even the first step. AI-based chatbots can help make the process more accessible by streamlining the application process.
Creating optimization in credit scoring
Credit scoring shouldn’t be a black and white process, but that doesn’t mean it has to be complicated. AI technology that is correctly implemented and carefully chosen may help lending businesses optimize their credit scoring process, create tailored loans and provide scoring free of human biases. This may include optimizing systems related to the risk of default, adding custom repayment rates or adjusting for the risk of an individual or business.
Instead, inclusivity is the way forward in banking. By focusing on sustainable, inclusive lending, led by AI technology, credit providers can access a broader market and provide services to lower-income Americans and other marginalized groups in a more responsible way.
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